Industrial Plant Machine Learning System

Abstract

An industrial plant machine learning system includes a machine learning model, providing machine learning data, an industrial plant providing plant data and an abstraction layer, connecting the machine learning model and the industrial plant, wherein the abstraction layer is configured to provide standardized communication between the machine learning model and the industrial plant, using a machine learning markup language.

What is claimed is: 
     
         1 . An industrial plant machine learning system, comprising:
 a machine learning model providing machine learning data;   an industrial plant providing plant data; and   an abstraction layer connecting the machine learning model and the industrial plant;   wherein the abstraction layer is configured to provide standardized communication between the machine learning model and the industrial plant using a machine learning markup language.   
     
     
         2 . The system of  claim 1 , wherein the abstraction layer is configured to enrich the received plant data with context data, and wherein the context data comprises plant states. 
     
     
         3 . The system of  claim 2 , wherein the industrial plant comprises a distributed control system (DCS), and wherein the abstraction layer is configured to determine the context data by analyzing a code of the DCS to automatically generate a finite state machine for auto-generating the plant states. 
     
     
         4 . The system of  claim 3 , wherein the abstraction layer is configured to use a code expression tree analysis for analyzing the code of the DCS. 
     
     
         5 . The system of  claim 2 , wherein the machine learning model is configured to use the plant states as labels for training the machine learning model. 
     
     
         6 . The system of  claim 1 , wherein the abstraction layer is configured to abstract the machine learning data and the plant data. 
     
     
         7 . The system of  claim 1 , wherein a connection between the abstraction layer and the industrial plant uses a platform-independent communication technology. 
     
     
         8 . The system of  claim 7 , wherein the platform-independent communication technology comprises one of: OPC Unified Architecture (OPC UA) or Message Queuing Telemetry Transport (MQTT). 
     
     
         9 . The system of  claim 6 , wherein abstracting the plant data comprises standardizing and abstracting vendor specific parts and industrial plant specific parts using the machine learning markup language. 
     
     
         10 . The system of  claim 1 , wherein the abstraction layer is located in an edge device located near the industrial plant. 
     
     
         11 . The system of  claim 1 , wherein the abstraction layer comprises an application programming interface (API) that provides standardized access to the plant data. 
     
     
         12 . The system of  claim 11 , wherein the API comprises an access control unit providing access control for a user to the industrial plant data and the machine learning data. 
     
     
         13 . A method for industrial plant machine learning communication, comprising:
 providing, by a machine learning model, machine learning data;   providing, by an industrial plant, plant data; and   providing, by an abstraction layer that connects the machine learning model and the industrial plant, standardized communication between the machine learning model and the industrial plant using a machine learning markup language.   
     
     
         14 . The method of  claim 13 , wherein the abstraction layer is configured to enrich the received plant data with context data, and wherein the context data comprises plant states. 
     
     
         15 . The method of  claim 14 , wherein the industrial plant comprises a distributed control system (DCS), and wherein the method further comprises using the abstraction layer to determine the context data by analyzing a code of the DCS to automatically generate a finite state machine for auto-generating the plant states. 
     
     
         16 . The method of  claim 15 , further comprises causing the abstraction layer to use a code expression tree analysis for analyzing the code of the DCS. 
     
     
         17 . The method of  claim 14 , further comprising using the plant states as labels for training the machine learning model in the machine learning model. 
     
     
         18 . The method of  claim 13 , further comprising using the abstraction layer to abstract the machine learning data and the plant data. 
     
     
         19 . The method of  claim 18 , wherein abstracting the plant data comprises standardizing and abstracting vendor specific parts and industrial plant specific parts using the machine learning markup language. 
     
     
         20 . The method of  claim 13 , wherein the abstraction layer is located in an edge device located near the industrial plant.